Detection of EGFR mutations in early-stage lung adenocarcinoma by machine learning-based radiomics.

ABSTRACT:

Background

We hypothesized that epidermal growth factor receptor (EGFR) mutations could be detected in early-stage lung adenocarcinoma using radiomics.

Methods

This retrospective study included consecutive patients with clinical stage I/II lung adenocarcinoma who underwent curative-intent pulmonary resection from March-December 2016. Using preoperative enhanced chest computed tomography, 3,951 radiomic features were extracted in total from the tumor (area within the tumor boundary), tumor rim (area within ±3 mm of the tumor boundary), and tumor exterior (area between +10 mm outside the tumor and tumor boundary). A machine learning-based radiomics model was constructed to detect EGFR mutations. The combined model incorporated both radiomic and clinical features

SUBMITTER: Omura K 

PROVIDER: S-EPMC10174757 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature